﻿* Encoding: UTF-8.

*****This file includes the SPSS syntax for the descriptive analyses and variable recoding. 
*The inferential statistics were executed in STATA

*****Syntax for Table 1. Perceptions and Attitudes about Gender Favoritism of American Adults*****

*among men

temporary.
select if (male_3=1).
fre FFW_1_3 FFW_2_3 FFW_3_3 FFW_4_3 FFWa_3. 

*among women

temporary.
select if (male_3=0).
fre FFW_1_3 FFW_2_3 FFW_3_3 FFW_4_3 FFWa_3. 

*not shown in table--robustness check using weights

Weight by Weight_3. 
temporary.
select if (male_3=1).
fre FFW_1_3 FFW_2_3 FFW_3_3 FFW_4_3 FFWa_3. 
WEIGHT OFF.

Weight by Weight_3. 
temporary.
select if (male_3=0).
fre FFW_1_3 FFW_2_3 FFW_3_3 FFW_4_3 FFWa_3. 
WEIGHT OFF.

*****Syntax for Tables 3 and 4: Wave 3 Intentions by Wave 1 Vote Intentions among Male & Female Democrats

CROSSTABS
  /TABLES=firstdem3_3 BY firstdem3_1 BY male_1 
  /FORMAT=AVALUE TABLES
  /STATISTICS=CHISQ CC PHI LAMBDA 
  /CELLS=COUNT COLUMN 
  /COUNT ROUND CELL.

***********Variable Recoding********

******Perceptions of Gender Favoritism (waves 1 and 3)

**wave 1

*recoding of individual items

fre FFW_1_1 FFW_2_1 FFW_3_1 FFW_4_1. 

fre FFW_1_1.
recode FFW_1_1 (1=4) (2=3) (4=1) (3=2) into FFW1_1. 
variable labels FFW1_1 "Female elected officials are more likely to... Favor women for government jobs over male applicants".
value labels FFW1_1 4 "strongly agree" 3 "somewhat agree" 2 "somewhat disagree" 1 "strongly disagree".
fre FFW1_1. 

fre FFW_2_1. 
recode FFW_2_1 (1=4) (2=3) (4=1) (3=2) into FFW2_1. 
variable labels FFW2_1 "Female elected officials are more likely to... Promote educational programs targeted at girls at the expense of boys".
value labels FFW2_1 4 "strongly agree" 3 "somewhat agree" 2 "somewhat disagree" 1 "strongly disagree".
fre FFW2_1. 

fre FFW_3_1. 
recode FFW_3_1 (1=4) (2=3) (4=1) (3=2) into FFW3_1. 
variable labels FFW3_1 "Female elected officials are more likely to... Support government spending that favors women".
value labels FFW3_1 4 "strongly agree" 3 "somewhat agree" 2 "somewhat disagree" 1 "strongly disagree".
fre FFW3_1.

fre FFW_4_1. 
recode FFW_4_1 (1=4) (2=3) (4=1) (3=2) into FFW4_1. 
variable labels FFW4_1 "Female elected officials are more likely to... Focus on issues that mainly affect women".
value labels FFW4_1 4 "strongly agree" 3 "somewhat agree" 2 "somewhat disagree" 1 "strongly disagree".
fre FFW4_1.

*cronbach's alpha of 4-item scale

RELIABILITY
  /VARIABLES=FFW1_1, FFW2_1, FFW3_1, FFW4_1
  /SCALE('ALL VARIABLES') ALL
  /MODEL=ALPHA.

correlations FFW1_1, FFW2_1, FFW3_1, FFW4_1. 

*4-item scale with 1-4 range

compute FFWperceptions_1=mean(FFW1_1, FFW2_1, FFW3_1, FFW4_1).
variable labels FFWperceptions_1 "scale of perceptions of gender favoritism w1". 
descriptives FFWperceptions_1. 

*4-item scale with 0-1 range (used in the analyses)

compute FFWperceptionsZ1_1=(FFWperceptions_1-1)/3. 
variable labels FFWperceptionsZ1_1 "scale of perceptions of gender favoritism w1 0-1 range". 
descriptives FFWperceptionsZ1_1.

**wave 3

*recoding of individual items

fre FFW_1_3.
missing values FFW_1_3(-1,-3). 
fre FFW_1_3.
recode FFW_1_3 (1=4) (2=3) (4=1) (3=2) into FFW1_3. 
variable labels FFW1_3 "Female elected officials are more likely to... Favor women for government jobs over male applicants".
value labels FFW1_3 4 "strongly agree" 3 "somewhat agree" 2 "somewhat disagree" 1 "strongly disagree".
fre FFW1_3. 

fre FFW_2_3. 
missing values FFW_2_3(-1,-3). 
fre FFW_2_3.
recode FFW_2_3 (1=4) (2=3) (4=1) (3=2) into FFW2_3. 
variable labels FFW2_3 "Female elected officials are more likely to... Promote educational programs targeted at girls at the expense of boys".
value labels FFW2_3 4 "strongly agree" 3 "somewhat agree" 2 "somewhat disagree" 1 "strongly disagree".
fre FFW2_3. 

fre FFW_3_3. 
missing values FFW_3_3(-1,-3). 
fre FFW_3_3.
recode FFW_3_3 (1=4) (2=3) (4=1) (3=2) into FFW3_3. 
variable labels FFW3_3 "Female elected officials are more likely to... Support government spending that favors women".
value labels FFW3_3 4 "strongly agree" 3 "somewhat agree" 2 "somewhat disagree" 1 "strongly disagree".
fre FFW3_3.

fre FFW_4_3. 
missing values FFW_4_3(-1,-3). 
fre FFW_4_3.
recode FFW_4_3 (1=4) (2=3) (4=1) (3=2) into FFW4_3. 
variable labels FFW4_3 "Female elected officials are more likely to... Focus on issues that mainly affect women".
value labels FFW4_3 4 "strongly agree" 3 "somewhat agree" 2 "somewhat disagree" 1 "strongly disagree".
fre FFW4_3.

*cronbach's alpha of 4-item scale

RELIABILITY
  /VARIABLES=FFW1_3, FFW2_3, FFW3_3, FFW4_3
  /SCALE('ALL VARIABLES') ALL
  /MODEL=ALPHA.

correlations FFW1_3, FFW2_3, FFW3_3, FFW4_3. 

*4-item scale with 1-4 range

compute FFWperceptions_3=mean(FFW1_3, FFW2_3, FFW3_3, FFW4_3).
variable labels FFWperceptions_3 "scale of perceptions of gender favoritism w3". 
descriptives FFWperceptions_3. 
fre FFWperceptions_3. 

*4-item scale with 0-1 range (used in the analyses)

compute FFWperceptionsZ1_3=(FFWperceptions_3-1)/3. 
variable labels FFWperceptionsZ1_3 "scale of perceptions of gender favoritism w3 0-1 range". 
descriptives FFWperceptionsZ1_3.


******Attitudes about Gender Favoritism (wave 3)

fre FFWa_3. 
missing values FFWa_3(-1,-3).
fre FFWa_3.
compute FFWattitudes_3=FFWa_3. 
variable labels FFWattitudes_3 "Thinking about the statements you just read, would it be good or bad if female elected officials favored women?".
value labels FFWattitudes_3 1 "very good" 2 "somewhat good" 3 "somewhat bad" 4 "very bad". 
fre FFWattitudes_3. 

*coding to the 0-1 range (used in the analyses)

compute FFWattitudesZ1_3=(FFWattitudes_3-1)/3.
variable labels FFWattitudesZ1_3 "attitudes about gender favoritism w3 0-1 range".
descriptives FFWattitudesZ1_3. 


******Clinton Vote Choice (waves 1 and 3)

recode firstdem_1 (2=1) (1,3,4,5,6,7,8=0) into firstdemHC_1.
variable labels firstdemHC_1 "If you had to choose this week to vote for one of the primary candidates to be the presidential nominee for the Democratic party, which candidate would you vote for:".
value labels firstdemHC_1 1 "Hillary Clinton" 0 "any other candidate". 
fre firstdemHC_1. 

recode VP1A_DEM_3 (1=1) (2=0) into firstdemHC_3. 
variable labels firstdemHC_3  "If you had to choose this week to vote for one of the primary candidates to be the presidential nominee for the Democratic party, which candidate would you vote for:".
value labels firstdemHC_3 1 "Hillary Clinton" 0 "Barack Obama".
fre firstdemHC_3. 


******Perceptions of Racial Favoritism (waves 1 and 3)

fre FFB_1_1. 
recode FFB_1_1 (1=4)  (2=3) (4=1) (3=2) into FFB1_1.
variable labels FFB1_1 "Black elected officials are more likely to Favor blacks for government jobs over white applicants".
value labels FFB1_1 4 "strongly agree" 3 "somewhat agree" 2 "somewhat disagree" 1 "strongly disagree".
fre FFB1_1.  

fre FFB_2_1. 
recode FFB_2_1 (1=4)  (2=3) (4=1) (3=2) into FFB2_1.
variable labels FFB2_1 "Black elected officials are more likely to... Support government spending that favors blacks".
value labels FFB2_1 4 "strongly agree" 3 "somewhat agree" 2 "somewhat disagree" 1 "strongly disagree".
fre FFB2_1.  

fre FFB_3_1. 
recode FFB_3_1 (1=4)  (2=3) (4=1) (3=2) into FFB3_1.
variable labels FFB3_1 "Black elected officials are more likely to... Support policies that could cost whites jobs".
value labels FFB3_1 4 "strongly agree" 3 "somewhat agree" 2 "somewhat disagree" 1 "strongly disagree".
fre FFB3_1.  

fre FFB_4_1. 
recode FFB_4_1 (1=4)  (2=3) (4=1) (3=2) into FFB4_1.
variable labels FFB4_1 "Black elected officials are more likely to... Give special favors to the black community".
value labels FFB4_1 4 "strongly agree" 3 "somewhat agree" 2 "somewhat disagree" 1 "strongly disagree".
fre FFB4_1.  

compute perceivedFFB_1=mean(FFB1_1, FFB2_1, FFB3_1, FFB4_1). 
variable labels perceivedFFB_1 "perceptions of racial favoritism scale wave 1".
value labels perceivedFFB_1 4 "strongly agree" 3 "somewhat agree" 2 "somewhat disagree" 1 "strongly disagree".
fre perceivedFFB_1. 

compute perceivedFFBZ1_1=(perceivedFFB_1-1)/3. 
variable labels perceivedFFBZ1_1 "perceptions of racial favoritism scale 0-1 range wave 1".
value labels perceivedFFBZ1_1 0 "perceive little racial favoritism" 1 "perceive a lot of racial favoritism".
fre perceivedFFBZ1_1. 

RELIABILITY
  /VARIABLES=FFB1_1, FFB2_1, FFB3_1, FFB4_1
  /SCALE('ALL VARIABLES') ALL
  /MODEL=ALPHA.

fre FFB_1_3. 
missing values FFB_1_3(-1). 
recode FFB_1_3 (1=4)  (2=3) (4=1) (3=2) into FFB1_3.
variable labels FFB1_3 "Black elected officials are more likely to Favor blacks for government jobs over white applicants".
value labels FFB1_3 4 "strongly agree" 3 "somewhat agree" 2 "somewhat disagree" 1 "strongly disagree".
fre FFB1_3.  

fre FFB_2_3. 
missing values FFB_2_3(-1). 
recode FFB_2_3 (1=4)  (2=3) (4=1) (3=2) into FFB2_3.
variable labels FFB2_3 "Black elected officials are more likely to... Support government spending that favors blacks".
value labels FFB2_3 4 "strongly agree" 3 "somewhat agree" 2 "somewhat disagree" 1 "strongly disagree".
fre FFB2_3.  

fre FFB_3_3. 
missing values FFB_3_3(-1). 
recode FFB_3_3 (1=4)  (2=3) (4=1) (3=2) into FFB3_3.
variable labels FFB3_3 "Black elected officials are more likely to... Support policies that could cost whites jobs".
value labels FFB3_3 4 "strongly agree" 3 "somewhat agree" 2 "somewhat disagree" 1 "strongly disagree".
fre FFB3_3.  

fre FFB_4_3. 
missing values FFB_4_3(-1). 
recode FFB_4_3 (1=4)  (2=3) (4=1) (3=2) into FFB4_3.
variable labels FFB4_3 "Black elected officials are more likely to... Give special favors to the black community".
value labels FFB4_3 4 "strongly agree" 3 "somewhat agree" 2 "somewhat disagree" 1 "strongly disagree".
fre FFB4_3.  

compute perceivedFFB_3=mean(FFB1_3, FFB2_3, FFB3_3, FFB4_3). 
variable labels perceivedFFB_3 "perceptions of racial favoritism scale wave 3".
value labels perceivedFFB_3 4 "strongly agree" 3 "somewhat agree" 2 "somewhat disagree" 1 "strongly disagree".
fre perceivedFFB_3. 

compute perceivedFFBZ1_3=(perceivedFFB_3-1)/3. 
variable labels perceivedFFBZ1_3 "perceptions of racial favoritism scale 0-1 range wave 3".
value labels perceivedFFBZ1_3 0 "perceive little racial favoritism" 1 "perceive a lot of racial favoritism".
fre perceivedFFBZ1_3. 

RELIABILITY
  /VARIABLES=FFB1_3, FFB2_3, FFB3_3, FFB4_3
  /SCALE('ALL VARIABLES') ALL
  /MODEL=ALPHA.

******Attitudes about Racial Favoritism (wave 3)

fre FFBa_3. 
missing values FFBa_3(-1).
fre FFBa_3.
compute attitudeFFB_3=FFBa_3. 
variable labels attitudeFFB_3 "Thinking about the statements you just read, would it be good or bad if black elected officials favored blacks?".
value labels attitudeFFB_3 1 "very good" 2 "somewhat good" 3 "somewhat bad" 4 "very bad". 
fre attitudeFFB_3. 

compute attitudeFFBZ1_3=(attitudeFFB_3-1)/3.
variable labels attitudeFFBZ1_3 "attitudes about racial favoritism w3 0-1 range".
value labels attitudeFFBZ1_3 0 "racial favoritism very good" 1 "racial favoritism very bad".
fre attitudeFFBZ1_3. 

*******Party Identification

fre party7_updated_1. 
recode party7_updated_1 (7=0) (6=1) (5=2) (4=3) (3=4) (2=5) (1=6) into pid7_1.
variable labels pid7_1 "6-point pid scale w1".
value labels pid7_1 0 "strong democrat" 1 "not strong democrat" 2 "leans democrat" 3 "undecided/indy/other" 4 "leans republican" 5 "not strong republican" 6 "strong republican".
fre pid7_1.

compute pid7Z1_1=pid7_1/6.
variable labels pid7Z1_1 "6-point pid scale w1 0-1 range".
fre pid7Z1_1.
value labels pid7Z1_1 0 "strong democrat" .17 "not strong democrat" .33 "leans democrat" .50 "undecided/indy/other" .67 "leans republican" .83 "not strong republican" 1 "strong republican".
fre pid7Z1_1.

fre pid7_1. 
recode pid7_1 (3=0) (2,4=1) (1,5=2) (0,6=3) into pidstrength_1.
value labels pidstrength_1 0 "undecided/indy/other" 1 "leaner" 2 "weak partisan" 3 "strong partisan".
fre pidstrength_1.
compute pidstrengthZ1_1=pidstrength_1/3. 
value labels pidstrengthZ1_1 0 "undecided/indy/other" .33 "leaner" .67 "weak partisan" 1 "strong partisan".
fre pidstrengthZ1_1. 

recode pid7_1 (0,1,2=0) (3=.5) (4,5,6=1) into pid3_1.
value labels pid3_1 0 "lean/weak/strong democrat" .5 "undecided/indy/other" 1 "lean/weak/strong republican". 
fre pid7_1 pid3_1. 

fre PARTY7_NEW_2.
fre Q7_2 Q8_2 Q9_2 Q10_2 . 
recode party7_new_2 (7=0) (6=1) (5=2) (4=3) (3=4) (2=5) (1=6) into pid7_2.
variable labels pid7_2 "6-point pid scale w2".
value labels pid7_2 0 "strong democrat" 1 "not strong democrat" 2 "leans democrat" 3 "undecided/indy/other" 4 "leans republican" 5 "not strong republican" 6 "strong republican".
fre pid7_2.

compute pid7Z1_2=pid7_2/6.
variable labels pid7Z1_2 "6-point pid scale w2 0-1 range".
value labels pid7Z1_2 0 "strong democrat" .17 "not strong democrat" .33 "leans democrat" .50 "undecided/indy/other" .67 "leans republican" .83 "not strong republican" 1 "strong republican".
fre pid7Z1_2.

fre pid7_2. 
recode pid7_2 (3=0) (2,4=1) (1,5=2) (0,6=3) into pidstrength_2.
value labels pidstrength_2 0 "undecided/indy/other" 1 "leaner" 2 "weak partisan" 3 "strong partisan".
fre pidstrength_2.
compute pidstrengthZ1_2=pidstrength_2/3. 
value labels pidstrengthZ1_2 0 "undecided/indy/other" .33 "leaner" .67 "weak partisan" 1 "strong partisan".
fre pidstrengthZ1_2. 

recode pid7_2 (0,1,2=0) (3=.5) (4,5,6=1) into pid3_2.
value labels pid3_2 0 "lean/weak/strong democrat" .5 "undecided/indy/other" 1 "lean/weak/strong republican". 
fre pid7_2 pid3_2. 

fre party7_updated_3. 
recode party7_updated_3 (7=0) (6=1) (5=2) (4=3) (3=4) (2=5) (1=6) into pid7_3.
variable labels pid7_3 "6-point pid scale w3".
value labels pid7_3 0 "strong democrat" 1 "not strong democrat" 2 "leans democrat" 3 "undecided/indy/other" 4 "leans republican" 5 "not strong republican" 6 "strong republican".
fre pid7_3.

compute pid7Z1_3=pid7_3/6.
variable labels pid7Z1_3 "6-point pid scale w3 0-1 range".
fre pid7Z1_3.
value labels pid7Z1_3 0 "strong democrat" .17 "not strong democrat" .33 "leans democrat" .50 "undecided/indy/other" .67 "leans republican" .83 "not strong republican" 1 "strong republican".
fre pid7Z1_3.

fre pid7_3. 
recode pid7_3 (3=0) (2,4=1) (1,5=2) (0,6=3) into pidstrength_3.
value labels pidstrength_3 0 "undecided/indy/other" 1 "leaner" 2 "weak partisan" 3 "strong partisan".
fre pidstrength_3.
compute pidstrengthZ1_3=pidstrength_3/3. 
value labels pidstrengthZ1_3 0 "undecided/indy/other" .33 "leaner" .67 "weak partisan" 1 "strong partisan".
fre pidstrengthZ1_3. 

recode pid7_3 (0,1,2=0) (3=.5) (4,5,6=1) into pid3_3.
value labels pid3_3 0 "lean/weak/strong democrat" .5 "undecided/indy/other" 1 "lean/weak/strong republican". 
fre pid7_3 pid3_3. 

******Race (black)

fre ppethm_1. 
recode ppethm_1 (2=1) (1,3,4,5=0) into black_1.
value labels black_1 0 "not black" 1 "non-hispanic black".
fre black_1. 

fre ppethm_3. 
recode ppethm_3 (2=1) (1,3,4,5=0) into black_3.
value labels black_3 0 "not black" 1 "non-hispanic black".
fre black_3. 

******Gender (male)

recode ppgender_1 (2=0) (1=1) into male_1.
value labels male_1 0 "female" 1 "male".
fre ppgender_1 male_1. 

recode ppgender_3 (2=0) (1=1) into male_3.
value labels male_3 0 "female" 1 "male".
fre ppgender_3 male_3. 

*******Education

fre ppeduc_1. 
recode ppeduc_1 (1,2=0) (3=1) (4,5=2) (6=3) (7,8,9=4) into educ_1.
variable labels educ_1 "levels of formal education w1".
value labels educ_1 0 "less than high school" 1 "hs diploma or ged" 2 "some college or associate's" 3 "BA degree" 4 "MA, prof, or phd".
fre educ_1.  

compute educZ1_1=educ_1/4.
variable labels educZ1_1 "levels of formal education w1 0-1 range".
value labels educZ1_1 0 "less than high school" .25 "hs diploma or ged" .5 "some college or associate's" .75 "BA degree" 1 "MA, prof, or phd".
fre educZ1_1.

fre ppeduc_3. 
recode ppeduc_3 (1,2,3,4,5,6,7,8=0) (9=1) (10,11=2) (12=3) (13,14=4) into educ_3.
variable labels educ_3 "levels of formal education w3".
value labels educ_3 0 "less than high school" 1 "hs diploma or ged" 2 "some college or associate's" 3 "BA degree" 4 "MA, prof, or phd".
fre educ_3.  

compute educZ1_3=educ_3/4.
variable labels educZ1_3 "levels of formal education w3 0-1 range".
value labels educZ1_3 0 "less than high school" .25 "hs diploma or ged" .5 "some college or associate's" .75 "BA degree" 1 "MA, prof, or phd".
fre educZ1_3.

*Income

fre PPINCIMP_1.
recode ppincimp_1 (1=2.5) (2=6.25) (3=8.75) (4=11.25) (5=13.75) (6=17.5) (7=22.5) (8=27.5) 
(9=32.5) (10=37.5) (11=45) (12=55) (13=67.5) (14=80) (15=92.5) (16=112.5) (17=137.5) (18=167.5) (19=225) into income_1.
fre income_1.

compute incomeZ1_1=(income_1-2.5)/222.5.
fre incomeZ1_1.

fre ppincimp_3.
recode ppincimp_3 (1=2.5) (2=6.25) (3=8.75) (4=11.25) (5=13.75) (6=17.5) (7=22.5) (8=27.5) 
(9=32.5) (10=37.5) (11=45) (12=55) (13=67.5) (14=80) (15=92.5) (16=112.5) (17=137.5) (18=167.5) (19=225) into income_3.
fre income_3.

compute incomeZ1_3=(income_3-2.5)/222.5.
fre incomeZ1_3.

*Age

fre ppage_1.
compute ageZ1_1=(ppage_1-18)/78.
fre ageZ1_1.
correlations ppage_1 ageZ1_1.

fre ppage_3.
compute ageZ1_3=(ppage_3-18)/92.
fre ageZ1_3.
correlations ppage_3 ageZ1_3.

*Region (south) (11 states of the former confederacy)

*Alabama (63), Arkansas (71), Georgia (58), Florida (59), Louisiana (72), Mississippi (64), North Carolina (56), South Carolina (57), Texas (74), Virginia (54), Tennessee (62)

fre ppstaten_1. 
recode ppstaten_1 (63,71,58,59,72,64,56,57,74,54,62=1) (11,12,13,14,15,16,21,22,23,31,32,33,34,35,41,42,43,44,45,46,47,51,52,53,55,61,73,81,82,83,84,85,86,87,88,91,92,93,94,95=0) into oldsouth_1.
variable labels oldsouth_1 "11 states of the former confederacy".
value labels oldsouth_1 1 "AL, GA, LA,VA, NC, FL, SC, TN, AR, TX, MS" 0 "all other states".
fre oldsouth_1.

fre ppstaten_3. 
recode ppstaten_3 (63,71,58,59,72,64,56,57,74,54,62=1) (11,12,13,14,15,16,21,22,23,31,32,33,34,35,41,42,43,44,45,46,47,51,52,53,55,61,73,81,82,83,84,85,86,87,88,91,92,93,94,95=0) into oldsouth_3.
variable labels oldsouth_3 "11 states of the former confederacy".
value labels oldsouth_3 1 "AL, GA, LA,VA, NC, FL, SC, TN, AR, TX, MS" 0 "all other states".
fre oldsouth_3.

********Campaign Contact

fre AG3_1_1 AG3_2_1 AG3_3_1 AG3_4_1 AG3_5_1 AG3_6_1.
compute campcontact_1=sum(AG3_1_1, AG3_2_1, AG3_3_1, AG3_4_1).  
fre campcontact_1. 
compute campcontactZ1_1=campcontact_1/4.
fre campcontactZ1_1. 

fre AG3_1_3 AG3_2_3 AG3_3_3 AG3_4_3 AG3_5_3.
compute campcontact_3=sum(AG3_1_3, AG3_2_3, AG3_3_3, AG3_4_3).
fre campcontact_3. 
compute campcontactZ1_3=campcontact_3/4.
fre campcontactZ1_3. 

********Political Interest 

recode pppa0004_1 (1=1) (2=.67) (3=.33) (4=0) into polinterest_1.
value labels polinterest_1 0 "not at all interested" .33 "slightly interested" .67 "somewhat interested" 1 "very interested".
fre pppa0004_1 polinterest_1. 

recode Q16_3 (1=1) (2=.67) (3=.33) (4=0) into polinterest_3.
value labels polinterest_3 0 "not at all interested" .33 "slightly interested" .67 "somewhat interested" 1 "very interested".
fre Q16_3 polinterest_3. 

*******Perceived Viability of the Democratic Candidates

fre EX1A_1 EX1A_3. 
missing values EX1A_1 (-1).
fre EX1A_1. 
missing values EX1A_3 (-3 thru -1).
fre EX1A_3. 

fre EX1A_1.
recode EX1A_1 (2=1) (1,3,4,5,6,7,8=0) into viableDem_1. 
variable labels viableDem_1 "who do you think is most likely to win the Democratic nomination for president?".
value labels viableDem_1 1 "Hillary Clinton" 0 "another candidate".
fre viableDem_1.

fre EX1A_3. 
recode EX1A_3 (1=1) (2=0) into viableDem_3. 
variable labels viableDem_3 "who do you think is most likely to win the Democratic nomination for president?".
value labels viableDem_3 1 "Hillary Clinton" 0 "Obama".
fre viableDem_3.

*******Perceived Electability of the Democratic Candidates

fre EX9_1 EX9_3. 
missing values EX9_1 (-1, -4).
missing values EX9_3 (-3, -1).
fre EX9_1 EX9_3. 

fre EX9_1.
recode EX9_1 (2=1) (1,3,4,5,6,7,8=0) into electableDem_1.
variable labels electableDem_1 "which of the Dem candidates would give the Dem party the best chance in November?".
value labels electableDem_1 1 "Hillary Clinton" 0 "another candidate".
fre electableDem_1. 

fre EX9_3. 
recode EX9_3 (1=1) (2=0) into electableDem_3.
variable labels electableDem_3 "which of the Dem candidates would give the Dem party the best chance in November?".
value labels electableDem_3 1 "Hillary Clinton" 0 "Obama".
fre electableDem_3. 

********Perceived Issue Agreement: Clinton

*# of issues perceived favorably (0-6) minus # of issues perceived unfavorably (0-6)
*economy, homeland security, health care, Iraq, immigration, and trade

fre PSW1A_1_1 PSW2A_1_1 PSW3A_1_1 POS2A_1_1 POS5A_1_1 POS7A_1_1. 

compute HCissuegd6_1=sum(PSW1A_1_1, PSW2A_1_1, PSW3A_1_1, POS2A_1_1, POS5A_1_1, POS7A_1_1).
fre HCissuegd6_1. 

fre PSW1B_1_1 PSW2B_1_1 PSW3B_1_1 POS2B_1_1 POS5B_1_1 POS7B_1_1.

compute HCissuebd6_1=sum(PSW1B_1_1, PSW2B_1_1, PSW3B_1_1, POS2B_1_1, POS5B_1_1, POS7B_1_1).
fre HCissuebd6_1. 

fre HCissuegd6_1 HCissuebd6_1. 
compute HCissueprox6_1=HCissuegd6_1-HCissuebd6_1. 
fre HCissueprox6_1. 
compute HCissueprox6Z1_1=(HCissueprox6_1+6)/12. 
fre HCissueprox6Z1_1. 

fre PSW1A1_3 PSW2A1_3 PSW3A1_3 POS2A1_3 POS5A1_3 POS7A1_3.
missing values PSW1A1_3 PSW2A1_3 PSW3A1_3 POS2A1_3 POS5A1_3 POS7A1_3 (-3). 
fre PSW1A1_3 PSW2A1_3 PSW3A1_3 POS2A1_3 POS5A1_3 POS7A1_3.

compute HCissuegd6_3=sum(PSW1A1_3, PSW2A1_3, PSW3A1_3, POS2A1_3, POS5A1_3, POS7A1_3).
fre HCissuegd6_3. 

fre PSW1B1_3 PSW2B1_3 PSW3B1_3 POS2B1_3 POS5B1_3 POS7B1_3.
missing values PSW1B1_3 PSW2B1_3 PSW3B1_3 POS2B1_3 POS5B1_3 POS7B1_3 (-3). 
fre PSW1B1_3 PSW2B1_3 PSW3B1_3 POS2B1_3 POS5B1_3 POS7B1_3.

compute HCissuebd6_3=sum(PSW1B1_3, PSW2B1_3, PSW3B1_3, POS2B1_3, POS5B1_3, POS7B1_3).
fre HCissuebd6_3. 

fre HCissuegd6_3 HCissuebd6_3. 
compute HCissueprox6_3=HCissuegd6_3-HCissuebd6_3. 
fre HCissueprox6_3. 
compute HCissueprox6Z1_3=(HCissueprox6_3+6)/12. 
fre HCissueprox6Z1_3. 

********Perceived Issue Agreement: Edwards

*# of issues perceived favorably (0-6) minus # of issues perceived unfavorably (0-6)
*economy, homeland security, health care, Iraq, immigration, and trade

fre PSW1A_2_1 PSW2A_2_1 PSW3A_2_1 POS2A_2_1 POS5A_2_1 POS7A_2_1. 

compute JEissuegd6_1=sum(PSW1A_2_1, PSW2A_2_1, PSW3A_2_1, POS2A_2_1, POS5A_2_1, POS7A_2_1).
fre JEissuegd6_1. 

fre PSW1B_2_1 PSW2B_2_1 PSW3B_2_1 POS2B_2_1 POS5B_2_1 POS7B_2_1.

compute JEissuebd6_1=sum(PSW1B_2_1, PSW2B_2_1, PSW3B_2_1, POS2B_2_1, POS5B_2_1, POS7B_2_1).
fre JEissuebd6_1. 

fre JEissuegd6_1 JEissuebd6_1. 
compute JEissueprox6_1=JEissuegd6_1-JEissuebd6_1. 
fre JEissueprox6_1. 
compute JEissueprox6Z1_1=(JEissueprox6_1+6)/12. 
fre JEissueprox6Z1_1. 

********Perceived Issue Agreement: Obama

*# of issues perceived favorably (0-6) minus # of issues perceived unfavorably (0-6)
*economy, homeland security, health care, Iraq, immigration, and trade

fre PSW1A_6_1 PSW2A_6_1 PSW3A_6_1 POS2A_6_1 POS5A_6_1 POS7A_6_1. 

compute BOissuegd6_1=sum(PSW1A_6_1, PSW2A_6_1, PSW3A_6_1, POS2A_6_1, POS5A_6_1, POS7A_6_1).
fre BOissuegd6_1. 

fre PSW1B_6_1 PSW2B_6_1 PSW3B_6_1 POS2B_6_1 POS5B_6_1 POS7B_6_1.

compute BOissuebd6_1=sum(PSW1B_6_1, PSW2B_6_1, PSW3B_6_1, POS2B_6_1, POS5B_6_1, POS7B_6_1).
fre BOissuebd6_1. 

fre BOissuegd6_1 BOissuebd6_1. 
compute BOissueprox6_1=BOissuegd6_1-BOissuebd6_1. 
fre BOissueprox6_1. 
compute BOissueprox6Z1_1=(BOissueprox6_1+6)/12. 
fre BOissueprox6Z1_1. 

fre PSW1A2_3 PSW2A2_3 PSW3A2_3 POS2A2_3 POS5A2_3 POS7A2_3.

compute BOissuegd6_3=sum(PSW1A2_3, PSW2A2_3, PSW3A2_3, POS2A2_3, POS5A2_3, POS7A2_3).
fre BOissuegd6_3. 

fre PSW1B2_3 PSW2B2_3 PSW3B2_3 POS2B2_3 POS5B2_3 POS7B2_3.

compute BOissuebd6_3=sum(PSW1B2_3, PSW2B2_3, PSW3B2_3, POS2B2_3, POS5B2_3, POS7B2_3).
fre BOissuebd6_3. 

fre BOissuegd6_3 BOissuebd6_3. 
compute BOissueprox6_3=BOissuegd6_3-BOissuebd6_3. 
fre BOissueprox6_3. 
compute BOissueprox6Z1_3=(BOissueprox6_3+6)/12. 
fre BOissueprox6Z1_3. 

********Perceived Issue Agreement: McCain

*# of issues perceived favorably (0-6) minus # of issues perceived unfavorably (0-6)
*economy, homeland security, health care, Iraq, immigration, and trade

fre PSW1A3_3 PSW2A3_3 PSW3A3_3 POS2A3_3 POS5A3_3 POS7A3_3.

compute JMissuegd6_3=sum(PSW1A3_3, PSW2A3_3, PSW3A3_3, POS2A3_3, POS5A3_3, POS7A3_3).
fre JMissuegd6_3. 

fre PSW1B3_3 PSW2B3_3 PSW3B3_3 POS2B3_3 POS5B3_3 POS7B3_3.

compute JMissuebd6_3=sum(PSW1B3_3, PSW2B3_3, PSW3B3_3, POS2B3_3, POS5B3_3, POS7B3_3).
fre JMissuebd6_3. 

fre JMissuegd6_3 JMissuebd6_3. 
compute JMissueprox6_3=JMissuegd6_3-JMissuebd6_3. 
fre JMissueprox6_3. 
compute JMissueprox6Z1_3=(JMissueprox6_3+6)/12. 
fre JMissueprox6Z1_3. 

*********Relative Perceived Issue Agreement: HC vs. BO/JE (whoever's closest to Rs position)

fre HCissueprox6_1 BOissueprox6_1 JEissueprox6_1. 

if BOissueprox6_1>JEissueprox6_1 HCBOJEissue6_1=HCBOissue6Z1_1. 
if JEissueprox6_1>BOissueprox6_1 HCBOJEissue6_1=HCJEissue6Z1_1. 
if BOissueprox6_1=JEissueprox6_1 HCBOJEissue6_1=HCBOissue6Z1_1.
fre HCBOJEissue6_1. 
value labels HCBOJEissue6_1 0 "JE/BO rated more favorably" .5 "HC and JE/BO rated equally on the issues" 1 "HC rated more favorably".
variable labels HCBOJEissue6_1 "relative issue agreement: HC minus JE or BO (whoever's had more favorable score)".
fre HCBOJEissue6_1. 

fre HCBOissue6Z1_1 HCJEissue6Z1_1. 

fre HCBOissue6Z1_3. 
compute HCBOJEissue6_3=HCBOissue6Z1_3. 
value labels HCBOJEissue6_3 0 "BO rated more favorably" .5 "HC and BO rated equally on the issues" 1 "HC rated more favorably".
variable labels HCBOJEissue6_3 "relative issue agreement: HC minus BO".
fre HCBOJEissue6_3. 

********Relative Perceived Issue Agreement: HC vs. JM

fre HCissueprox6_3 JMissueprox6_3. 
compute HCJMissue6_3=HCissueprox6_3-JMissueprox6_3.
fre HCJMissue6_3. 
if HCJMissue6_3<0 HCJMissue6Z1_3=0. 
if HCJMissue6_3=0 HCJMissue6Z1_3=.5. 
if HCJMissue6_3>0 HCJMissue6Z1_3=1. 
variable labels HCJMissue6Z1_3 "relative issue agreement: HC minus JM". 
value labels HCJMissue6Z1_3 0 "JM rated more favorably" .5 "HC and JM rated equally on the issues" 1 "HC rated more favorably".
fre HCJMissue6_3 HCJMissue6Z1_3. 

*******Ideology

fre IDEOLOGY_UPDATED_1.
missing values ideology_updated_1(-1).
recode ideology_updated_1 (1=0) (2=1) (3=2) (4=3) (5=4) (6=5) (7=6) into ideo_1.
variable labels ideo_1 "political ideology w1".
value labels ideo_1 0 "extremely liberal" 1 "liberal" 2 "slightly liberal" 3 "moderate" 4 "slightly conservative" 5 "conservative" 6 "extremely conservative".
fre ideo_1.

compute ideoZ1_1=ideo_1/6.
variable labels ideoZ1_1 "political ideology w1 0-1 range".
value labels ideoZ1_1 0 "extremely liberal" .17 "liberal" .33 "slightly liberal" .50 "moderate" .67 "slightly conservative" .83 "conservative" 1 "extremely conservative".
fre ideoZ1_1.

fre IDEOLOGY_UPDATED_3.
missing values ideology_updated_3(-1).
recode ideology_updated_3 (1=0) (2=1) (3=2) (4=3) (5=4) (6=5) (7=6) into ideo_3.
variable labels ideo_3 "political ideology w3".
value labels ideo_3 0 "extremely liberal" 1 "liberal" 2 "slightly liberal" 3 "moderate" 4 "slightly conservative" 5 "conservative" 6 "extremely conservative".
fre ideo_3.

compute ideoZ1_3=ideo_3/6.
variable labels ideoZ1_3 "political ideology w3 0-1 range".
value labels ideoZ1_3 0 "extremely liberal" .17 "liberal" .33 "slightly liberal" .50 "moderate" .67 "slightly conservative" .83 "conservative" 1 "extremely conservative".
fre ideoZ1_3.

*Clinton Perceived Ideology 

fre PCK2_1_1 libconHC_1. 
compute libconHCZ1_1=(libconHC_1-1)/6.
fre libconHC_1 libconHCZ1_1. 
variable labels libconHCZ1_1 "Hillary Clinton--perceived ideology".
value labels libconHCZ1_1 0 "extremely liberal" .17 "liberal" .33 "slightly liberal" .50 "moderate, middle of the road" .67 "slightly conservative" .83 "conservative" 1 "extremely conservative".
fre libconHCZ1_1. 

fre PCK2_1_3.
missing values PCK2_1_3(-1, 8). 
fre PCK2_1_3. 
compute libconHC_3=PCK2_1_3.
variable labels libconHC_3 "Hillary Clinton--perceived ideology".
value labels libconHC_3 1 "extremely liberal" 2 "liberal" 3 "slightly liberal" 4 "moderate, middle of the road" 5 "slightly conservative" 6 "conservative" 7 "extremely conservative".
fre libconHC_3. 
compute libconHCZ1_3=(libconHC_3-1)/6.
fre libconHC_3 libconHCZ1_3. 
variable labels libconHCZ1_3 "Hillary Clinton--perceived ideology".
value labels libconHCZ1_3 0 "extremely liberal" .17 "liberal" .33 "slightly liberal" .50 "moderate, middle of the road" .67 "slightly conservative" .83 "conservative" 1 "extremely conservative".
fre libconHCZ1_3. 

*John Edwards Perceived Ideology

fre PCK2_2_1 libconJE_1.
compute libconJEZ1_1=(libconJE_1-1)/6.
variable labels libconJEZ1_1 "John Edwards--perceived ideology".
value labels libconJEZ1_1 0 "extremely liberal" .17 "liberal" .33 "slightly liberal" .50 "moderate, middle of the road" .67 "slightly conservative" .83 "conservative" 1 "extremely conservative".
fre libconJE_1 libconJEZ1_1. 

*Obama Perceived Ideology

fre PCK2_4_1 libconBO_1. 
compute libconBOZ1_1=(libconBO_1-1)/6.
fre libconBO_1 libconBOZ1_1. 
variable labels libconBOZ1_1 "Barack Obama--perceived ideology".
value labels libconBOZ1_1 0 "extremely liberal" .17 "liberal" .33 "slightly liberal" .50 "moderate, middle of the road" .67 "slightly conservative" .83 "conservative" 1 "extremely conservative".
fre libconBOZ1_1. 

fre PCK2_4_3. 
missing values PCK2_4_3(-1, 8). 
fre PCK2_4_3. 
compute libconBO_3=PCK2_4_3.
variable labels libconBO_3 "Barack Obama--perceived ideology".
value labels libconBO_3 1 "extremely liberal" 2 "liberal" 3 "slightly liberal" 4 "moderate, middle of the road" 5 "slightly conservative" 6 "conservative" 7 "extremely conservative".
fre libconBO_3. 
compute libconBOZ1_3=(libconBO_3-1)/6.
variable labels libconBOZ1_3 "Barack Obama--perceived ideology".
value labels libconBOZ1_3 0 "extremely liberal" .17 "liberal" .33 "slightly liberal" .50 "moderate, middle of the road" .67 "slightly conservative" .83 "conservative" 1 "extremely conservative".
fre libconBO_3 libconBOZ1_3. 

*John McCain Perceived Ideology

fre PCK2_8_3. 
missing values PCK2_8_3(-1, 8). 
fre PCK2_8_3. 
compute libconJM_3=PCK2_8_3.
variable labels libconJM_3 "John McCain--perceived ideology".
value labels libconJM_3 1 "extremely liberal" 2 "liberal" 3 "slightly liberal" 4 "moderate, middle of the road" 5 "slightly conservative" 6 "conservative" 7 "extremely conservative".
fre libconJM_3. 
compute libconJMZ1_3=(libconJM_3-1)/6.
variable labels libconJMZ1_3 "John McCain--perceived ideology".
value labels libconJMZ1_3 0 "extremely liberal" .17 "liberal" .33 "slightly liberal" .50 "moderate, middle of the road" .67 "slightly conservative" .83 "conservative" 1 "extremely conservative".
fre libconJM_3 libconJMZ1_3. 

*Ideological Proximity from Clinton 

fre PCK2_1_1 IDEOLOGY_UPDATED_1.
missing values PCK2_1_1 (-1, 8).
fre PCK2_1_1 IDEOLOGY_UPDATED_1.
compute ideoproxHC_1=IDEOLOGY_UPDATED_1-PCK2_1_1. 
fre ideoproxHC_1.
recode ideoproxHC_1 (0=0) (1,-1=1) (2,-2=2) (3,-3=3) (4,-4=4) (5,-5=5) (6,-6=6). 
fre ideoproxHC_1. 
missing values PCK2_1_1().
missing values IDEOLOGY_UPDATED_1(). 
fre PCK2_1_1 IDEOLOGY_UPDATED_1. 
if PCK2_1_1=-1 or PCK2_1_1=8 or IDEOLOGY_UPDATED_1=-1 ideoproxHC_1=3. 
fre ideoproxHC_1. 
compute ideoproxHCZ1_1=ideoproxHC_1/6. 
fre ideoproxHCZ1_1. 

fre PCK2_1_3 IDEOLOGY_UPDATED_3.
missing values PCK2_1_3(-1,8). 
missing values IDEOLOGY_UPDATED_3(-1). 
fre PCK2_1_3 IDEOLOGY_UPDATED_3.
compute ideoproxHC_3=IDEOLOGY_UPDATED_3-PCK2_1_3. 
fre ideoproxHC_3.
recode ideoproxHC_3 (0=0) (1,-1=1) (2,-2=2) (3,-3=3) (4,-4=4) (5,-5=5) (6,-6=6). 
fre ideoproxHC_3. 
missing values PCK2_1_3(-1).
missing values IDEOLOGY_UPDATED_3(). 
fre PCK2_1_3 IDEOLOGY_UPDATED_3. 
if PCK2_1_3=8 or IDEOLOGY_UPDATED_3=-1 ideoproxHC_3=3. 
fre ideoproxHC_3. 
compute ideoproxHCZ1_3=ideoproxHC_3/6. 
fre ideoproxHCZ1_3. 

*Ideological Proximity from Obama 

fre PCK2_4_1 IDEOLOGY_UPDATED_1.
missing values PCK2_4_1 (-1, 8).
missing values IDEOLOGY_UPDATED_1 (-1). 
fre PCK2_4_1 IDEOLOGY_UPDATED_1.
compute ideoproxBO_1=IDEOLOGY_UPDATED_1-PCK2_4_1. 
fre ideoproxBO_1.
recode ideoproxBO_1 (0=0) (1,-1=1) (2,-2=2) (3,-3=3) (4,-4=4) (5,-5=5) (6,-6=6). 
fre ideoproxBO_1. 
missing values PCK2_4_1().
missing values IDEOLOGY_UPDATED_1(). 
fre PCK2_4_1 IDEOLOGY_UPDATED_1. 
if PCK2_4_1=-1 or PCK2_4_1=8 or IDEOLOGY_UPDATED_1=-1 ideoproxBO_1=3. 
fre ideoproxBO_1. 
compute ideoproxBOZ1_1=ideoproxBO_1/6. 
fre ideoproxBOZ1_1. 

fre PCK2_4_3 IDEOLOGY_UPDATED_3.
missing values PCK2_4_3(-1,8). 
missing values IDEOLOGY_UPDATED_3(-1). 
fre PCK2_4_3 IDEOLOGY_UPDATED_3.
compute ideoproxBO_3=IDEOLOGY_UPDATED_3-PCK2_4_3. 
fre ideoproxBO_3.
recode ideoproxBO_3 (0=0) (1,-1=1) (2,-2=2) (3,-3=3) (4,-4=4) (5,-5=5) (6,-6=6). 
fre ideoproxBO_3. 
missing values PCK2_4_3(-1).
missing values IDEOLOGY_UPDATED_3(). 
fre PCK2_4_3 IDEOLOGY_UPDATED_3. 
fre ideoproxBO_3. 
if PCK2_4_3=8 or IDEOLOGY_UPDATED_3=-1 ideoproxBO_3=3. 
fre ideoproxBO_3. 
compute ideoproxBOZ1_3=ideoproxBO_3/6. 
fre ideoproxBOZ1_3. 

*Ideological Proximity from Edwards 

fre PCK2_2_1 IDEOLOGY_UPDATED_1.
missing values PCK2_2_1 (-1, 8).
missing values IDEOLOGY_UPDATED_1 (-1). 
fre PCK2_2_1 IDEOLOGY_UPDATED_1.
compute ideoproxJE_1=IDEOLOGY_UPDATED_1-PCK2_2_1. 
fre ideoproxJE_1.
recode ideoproxJE_1 (0=0) (1,-1=1) (2,-2=2) (3,-3=3) (4,-4=4) (5,-5=5) (6,-6=6). 
fre ideoproxJE_1. 
missing values PCK2_2_1().
missing values IDEOLOGY_UPDATED_1(). 
fre PCK2_2_1 IDEOLOGY_UPDATED_1. 
fre ideoproxJE_1.
if PCK2_2_1=-1 or PCK2_2_1=8 or IDEOLOGY_UPDATED_1=-1 ideoproxJE_1=3. 
fre ideoproxJE_1. 
compute ideoproxJEZ1_1=ideoproxJE_1/6. 
fre ideoproxJEZ1_1. 

*Ideological Proximity from John McCain 

fre PCK2_8_3 IDEOLOGY_UPDATED_3.
missing values PCK2_8_3(-1,8). 
missing values IDEOLOGY_UPDATED_3(-1). 
fre PCK2_8_3 IDEOLOGY_UPDATED_3.
compute ideoproxJM_3=IDEOLOGY_UPDATED_3-PCK2_8_3. 
fre ideoproxJM_3.
recode ideoproxJM_3 (0=0) (1,-1=1) (2,-2=2) (3,-3=3) (4,-4=4) (5,-5=5) (6,-6=6). 
fre ideoproxJM_3. 
fre PCK2_8_3 IDEOLOGY_UPDATED_3.
missing values PCK2_8_3(-1).
missing values IDEOLOGY_UPDATED_3(). 
fre PCK2_8_3 IDEOLOGY_UPDATED_3. 
fre ideoproxJM_3. 
if PCK2_8_3=8 or IDEOLOGY_UPDATED_3=-1 ideoproxJM_3=3. 
fre ideoproxJM_3. 
compute ideoproxJMZ1_3=ideoproxJM_3/6. 
fre ideoproxJMZ1_3. 

**************Relative Perceived Ideological Proximity: BO/JE vs. HC

fre ideoproxHC_1 ideoproxBO_1 ideoproxJE_1.
if ideoproxBO_1<ideoproxJE_1 ideoproxHCBOJE_1=ideoproxHCBOZ1_1. 
if ideoproxJE_1<ideoproxBO_1 ideoproxHCBOJE_1=ideoproxHCJEZ1_1.
if ideoproxBO_1=ideoproxJE_1 ideoproxHCBOJE_1=ideoproxHCBOZ1_1.
variable labels ideoproxHCBOJE_1 "perceived relative ideological proximity: JE/BO vs. HC (wave 1)".
value labels ideoproxHCBOJE_1 0 "perceive ideology as closer to JE/BO" .5 "perceive ideo of HC and JE/BO as same" 1 "perceive ideology as closer to HC".
fre ideoproxHCBOJE_1. 
fre ideoproxHCBOZ1_1 ideoproxHCJEZ1_1. 

compute ideoproxHCBOJE_3=ideoproxHCBOZ1_3. 
variable labels ideoproxHCBOJE_3 "perceived relative ideological proximity: BO vs. HC (wave 3)".
value labels ideoproxHCBOJE_3 0 "perceive ideology as closer to BO" .5 "perceive ideo to HC & BO as same" 1 "perceive ideology as closer to HC".
fre ideoproxHCBOJE_3 ideoproxHCBOZ1_3. 

*************Relative Perceived Ideological Proximity: JM vs. HC

fre ideoproxHC_3 ideoproxJM_3. 
compute ideoproxHCJM_3=ideoproxJM_3-ideoproxHC_3.
fre ideoproxHCJM_3. 
compute ideoproxHCJMZ1_3=(ideoproxHCJM_3+6)/12.
fre ideoproxHCJMZ1_3. 
variable labels ideoproxHCJMZ1_3 "perceived relative ideological proximity: JM vs. HC (wave 3)".
value labels ideoproxHCJMZ1_3 0 "perceive ideology as closer to JM" .5 "perceive ideo to HC & JM as same" 1 "perceive ideology as closer to HC".
fre ideoproxHCJMZ1_3. 




